• Cross-Cultural Studies
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• v.38
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• pp.29-63
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• 2015

This paper attempts to re-read Tennessee William's A Streetcar Named Desire from a non-Aristotelian perspective, particularly focusing on the audience performativity. In Chapter 6 of the Poetics, Aristotle says that tragedy has a final purpose or end (telos) and that is to inspire a catharsis (literally "purification") of pity and fear by means of representation and to give pleasure from experiencing their relief. However, a dramatic theoretician Augusto Boal argues that Aristotelian catharsis is not to get rid of pity and fear through their vehement discharge; rather, the basic function of catharsis is the purging of antisocial elements from the social body and the restoration of order because catharsis occurs when the spectator, terrified by the spectacle of the catastrophe, is purified of his "hamartia" which looks similar to the tragic flaw of the hero in the play. Thus, Boal asserts that Aristotle's coercive system of tragedy manipulates the emotions of the passive spectator. By contrast, in non-Aristotelian aesthetics, tragedy functions not as legitimation for a particular political configuration but as the performance of ethical acts-through which all the participants, including not only the actors but also the audience, communicate more actively about practical problems and actively work in order to make sense of themselves, others, and society. Here, the audience is required to restore and reinforce his/her capacity to think and to act; thus, an unquestioning, passive, indifferent attitude is not allowed. In these contexts, this paper explores how Tennessee William's A Streetcar Named Desire involves the audience in the responsibility for what occurs on the stage, in order to urge the audience's ethical judgements and responsible acts. This paper argues that what this play asks of us is not catharsis, the purging of pity and fear, but empathy toward the other's pain, beyond pity and fear, to carry out our responsibility of sharing in and caring for the other's suffering. That is to say that it will be an ethical way to "re-member" Blanche DuBoi-the iconic Williams victim "dis-membered" by traumatic memories and open wounds and is thus unable to complete her grieving and mourning-as one of us, not as the other. It will be the only way to remember right regarding her tragedy.

• Korean Journal of Remote Sensing
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• v.11 no.3
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• pp.101-116
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• 1995

The fact that the demands on traffic data collection are imposed by economic and safety considerations raisese the question of the potential for complementing existing traffic data collection programs with satellite data. Evaluating and monitoring traffic characteristics is becoming increasingly important as worsening congestion, declining economic situations, and increasing environmental sensitivies are forcing the government and municipalities to make better use of existing roadway capacities. The present system of using automatic counters at selected points on highways works well from a temporal point of view (i.e., during a specific period of time at one location). However, the present system does not cover the spatial aspects of the entire road system (i.e., for every location during specific periods of time); the counters are employed only at points and only on selected highways. This lack of spatial coverage is due, in part, to the cost of the automatic counters systems (fixed procurement and maintenance costs) and of the personal required to deploy them. The current procedure is believed to work fairly well in the aggregate mode, at the macro level. However, at micro level, the numbers are more suspect. In addition, the statistics only work when assuming a certain homogenity among characteristics of highways in the same class, an assumption that is impossible to test whn little or no data is gathered on many of the highways for a given class. In this paper, a remote sensing system as complement of the existing system is considered and implemented. Since satellite imagery with high resolution is not available, digitized panchromatic imagery acquired from an aircraft platform is utilized for initial test of the feasibility and performance capability of remote sensing data. Different levels of imagery resolutions are evaluated in an attempt to determine what vehicle types could be classified and counted against a background of pavement types, which might be expected in panchromatic satellite imagery. The results of a systematic study with three different levels of resolutions (1m, 2m and 4m) show that the panchromat ic reflectances of vehicles and pavements would be distributed so similarly that it would be difficult to classify systematically and analytically remotely sensing vehicles on pavement within panchromatic range. Anaysis of the aerial photographs show that the shadows of the vehicles could be a cue for vehicle detection.

• Journal of the Korean Society for Railway
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• v.18 no.6
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• pp.543-551
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• 2015

Quick-hardening track (QHT) is a construction method which is used to change from old ballast track to concrete track. Sufficient time for construction is important, as the construction should be done during operational breaks at night. Most of the time is spent on exchanging the ballast layer. If it is possible to apply the ballast non-exchange type of quick-hardening track, it would be more effective to reduce the construction time and costs. In this paper, pouring materials with high permeability are suggested and a construction method involving a layer separation pouring process considering the void condition is introduced in order to develop ballast non-exchange type of QHT. The separate pouring method can secure the required strength because optimized materials are poured into the upper layer and the lower layer for each void ratio condition. To ensure this process, a rheology analysis was conducted on the design of the pouring materials according to aggregate size, the aggregate distribution, the void ratio, the void size, the tortuosity and the permeability. A polymer series was used as the pouring material of the lower layer to secure the void filling capacity and for adhesion to the fine-grained layer. In addition, magnesium-phosphate ceramic (MPC) was used as the pouring material of the upper layer to secure the void-filling capacity and for adhesion of the coarse-grained layer. As a result of a mechanics test of the materials, satisfactory performance corresponding to existing quick-hardening track was noted.

• Korean Journal of Optics and Photonics
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• v.28 no.5
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• pp.213-220
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• 2017

This paper proposes how to fabricate an educational Mach-Zehnder interferometer that is easy to align and inexpensive, using 3D printers and semiconductor lasers. The interferometer consists of a body $165mm{\times}120mm{\times}57mm$ in size, mirror mounts, a laser holder, beam splitters, and so on. The laser path is adjusted by 4 mirror mounts, each comprised of rubber bands, small metal wires, and a screw. The interference fringe is enlarged by the lens at the final stage. The refractive index of a slide glass was measured by counting the number of moving interference fringes while the slide glass, inserted into one of the two interferometer arms, is rotating. The formula for the refractive index as a function of the optical-path difference and rotation angle was obtained, and used to calculate the refractive index of glass from the interferometer experiment. The use of a rotating glass in one arm of the interferometer nullifies the need for a precision stage, which despite its high cost is often required to observe the moving interference fringe in the classroom. Therefore, the 3D-printed Mach-Zehnder interferometer proposed in this paper can be very useful for education, because of its affordability and performance. It enables students to perform both qualitative and quantitative studies using a 3D-printed interferometer, such as measuring the refractive index of a glass sample, and the wavelength of light.

• Journal of Navigation and Port Research
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• v.45 no.4
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• pp.186-193
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• 2021

To enhance the competitiveness of the Busan Port in accordance with changes in global shipping and port industry trends, the Busan New Port is promoting step-by-step integration and developing a port resource-sharing platform. However, inefficient resource-sharing can cause unnecessary additional costs or impede port productivity, so accurate supply and demand matching of shared resources is required. In this study, the supply and demand of port resources were investigated for employees of Busan New Port and North Port, and port resources that could be ideally shared through IPA(Importance Performance Analysis) were analyzed. As a result of analyzing the equipment in the port, Yard Tractor, Reach Stacker, and Top Handler were the top considerations, and for facilities in the port, berths and aprons, empty container yards, and refrigerated container yards were the most important considerations. As for the data in the port, gate status, equipment specifications, and berth and apron conditions were the top considerations.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1685-1695
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• 2021

To generate a deep learning model with high performance, a large training dataset should be required. However, it requires a lot of time and cost to generate a large training dataset in remote sensing. Therefore, the importance of transfer learning of deep learning model using a small dataset have been increased. In this paper, we performed transfer learning of trained model based on open datasets by using orthoimages and digital maps to detect changes of building objects in multitemporal orthoimages. For this, an initial training was performed on open dataset for change detection through the HRNet-v2 model, and transfer learning was performed on dataset by orthoimages and digital maps. To analyze the effect of transfer learning, change detection results of various deep learning models including deep learning model by transfer learning were evaluated at two test sites. In the experiments, results by transfer learning represented best accuracy, compared to those by other deep learning models. Therefore, it was confirmed that the problem of insufficient training dataset could be solved by using transfer learning, and the change detection algorithm could be effectively applied to various remote sensed imagery.

• Journal of Digital Convergence
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• v.19 no.9
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• pp.33-42
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• 2021

Despite the importance of science education in an informal environment, the reality is that there is a lack of trend analysis research on 'Informal Science Learning (ISL)' and its effects. Therefore, the purpose of this paper is to find out the educational effects of ISL and how to use it, and to provide guidelines for future ISL research directions. This study classifies specific ISL-related papers published from 2010 to 2019 and compares them with each element of GLO used to measure the effectiveness of informal education. The fit of the analyzed data was checked for each part through SPSS and Chi-Square. In conclusion, it was found that researchers are using 'ISL' to pursue 'Knowledge and Understanding' and 'Attitudes and Values' among the five performance indicators of 'GLO'. On the other hand, 'Skills' and 'Enjoyment, Inspiration and Creativity' appear to have the least expectations, so supplementation is required in these areas in the future. In addition, this study intends to suggest a direction for informal science education-related program development and future research to various education workers.

• Journal of Bio-Environment Control
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• v.30 no.4
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• pp.393-400
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• 2021

Body weight of livestock is a crucial indicator for assessing feed requirements and nutritional status. This study was performed to estimate the body weight of Korean cattle (Hanwoo) using body volume determined from three-dimensional (3-D) image. A TOF camera with a resolution of 640×480 pixels, a frame rate of 44 fps and a field of view of 47°(H)×37°(V) was used to capture the 3-D images for Hanwoo. A grid image of the body was obtained through preprocessing such as separating the body from background and removing outliers from the obtained 3-D image. The body volume was determined by numerical integration using depth information to individual grid. The coefficient of determination for a linear regression model of body weight and body volume for calibration dataset was 0.8725. On the other hand, the coefficient of determination was 0.9083 in a multiple regression model for estimating body weight, in which the age of Hanwoo was added to the body volume as an explanatory variable. Mean absolute percentage error and root mean square error in the multiple regression model to estimate the body weight for validation dataset were 8.2% and 24.5kg, respectively. The performance of the regression model for weight estimation was improved and the effort required for estimating body weight could be reduced as the body volume of Hanwoo was used. From these results obtained, it was concluded that the body volume determined from 3-D of Hanwoo could be used as an effective variable for estimating body weight.

• Journal of the Korea Convergence Society
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• v.12 no.9
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• pp.11-19
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• 2021

A software system is required to change during its life cycle due to various requirements such as adding functionalities, fixing bugs, and adjusting to new computing environments. Such program code modification should be considered as carefully as a new system development becase unexpected software errors could be introduced. In addition, when reusing open source programs, we can expect higher quality software if code changes of the open source program are predicted in advance. This paper proposes a Convolutional Neural Network (CNN)-based deep learning model to predict source code changes. In this paper, the prediction of code changes is considered as a kind of a binary classification problem in deep learning and labeled datasets are used for supervised learning. Java projects and code change logs are collected from GitHub for training and testing datasets. Software metrics are computed from the collected Java source code and they are used as input data for the proposed model to detect code changes. The performance of the proposed model has been measured by using evaluation metrics such as precision, recall, F1-score, and accuracy. The experimental results show the proposed CNN model has achieved 95% in terms of F1-Score and outperformed the multilayer percept-based DNN model whose F1-Score is 92%.

• Microbiology and Biotechnology Letters
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• v.49 no.3
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• pp.413-424
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• 2021

In order to enhance rhizoremediation performance, which remediates contaminated soils using the interactions between plants and microorganisms in rhizosphere, it is required to develop effective microbial resources that simultaneously degrade contaminants and promote plant growth. In this study, heavy metal-resistant rhizobacteria, which had been cultivated in soils contaminated with heavy metals (copper, cadmium, and lead) and diesel were isolated from rhizospheres of maize and tall fescue. After that, the isolates were qualitatively evaluated for plant growth promoting (PGP) activities, heavy metal tolerance, and diesel degradability. As a result, six strains with heavy metal tolerance, PGP activities, and diesel degradability were isolated. Strains CuM5 and CdM2 were isolated from the rhizosphere soils of maize, and were identified as belonging to the genus Cupriavidus. From the rhizosphere soils of tall fescue, strains CuT6, CdT2, CdT5, and PbT3 were isolated and were identified as Fulvimonas soli, Cupriavidus sp., Novosphingobium sp., and Bacillus sp., respectively. Cupriavidus sp. CuM5 and CdM2 showed a low heavy metal tolerance and diesel degradability, but exhibited an excellent PGP ability. Among the six isolates, Cupriavidus sp. CdT2 and Bacillus sp. PbT3 showed the best diesel degradability. Additionally, Bacillus sp. PbT3 also exhibited excellent heavy metal tolerance and PGP abilities. These results indicate that the isolates can be used as promising microbial resources to promote plant growth and restore soils with contaminated heavy metals and diesel.